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title: 🔍ChatGPT Episodic and Semantic Memory Generator🏊 | |
emoji: 🌟GPT🔍 | |
colorFrom: green | |
colorTo: yellow | |
sdk: streamlit | |
sdk_version: 1.21.0 | |
app_file: app.py | |
pinned: true | |
license: mit | |
## ChatGPT Datasets 📚 | |
- WebText | |
- Common Crawl | |
- BooksCorpus | |
- English Wikipedia | |
- Toronto Books Corpus | |
- OpenWebText | |
## ChatGPT Datasets - Details 📚 | |
- **WebText:** A dataset of web pages crawled from domains on the Alexa top 5,000 list. This dataset was used to pretrain GPT-2. | |
- [WebText: A Large-Scale Unsupervised Text Corpus by Radford et al.](https://paperswithcode.com/dataset/webtext) | |
- **Common Crawl:** A dataset of web pages from a variety of domains, which is updated regularly. This dataset was used to pretrain GPT-3. | |
- [Language Models are Few-Shot Learners](https://paperswithcode.com/dataset/common-crawl) by Brown et al. | |
- **BooksCorpus:** A dataset of over 11,000 books from a variety of genres. | |
- [Scalable Methods for 8 Billion Token Language Modeling](https://paperswithcode.com/dataset/bookcorpus) by Zhu et al. | |
- **English Wikipedia:** A dump of the English-language Wikipedia as of 2018, with articles from 2001-2017. | |
- [Improving Language Understanding by Generative Pre-Training](https://huggingface.co/spaces/awacke1/WikipediaUltimateAISearch?logs=build) Space for Wikipedia Search | |
- **Toronto Books Corpus:** A dataset of over 7,000 books from a variety of genres, collected by the University of Toronto. | |
- [Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond](https://paperswithcode.com/dataset/bookcorpus) by Schwenk and Douze. | |
- **OpenWebText:** A dataset of web pages that were filtered to remove content that was likely to be low-quality or spammy. This dataset was used to pretrain GPT-3. | |
- [Language Models are Few-Shot Learners](https://paperswithcode.com/dataset/openwebtext) by Brown et al. | |